Cons - Tech Cons-AI and Quantitative Modelling-AI Data Scientist-Senior-Multiple Positions-1717770

 

Consulting - Technology Consulting - AI and Quantitative Modelling - Artificial Intelligence Data Scientist - Senior - Multiple Positions - 1717770, Ernst & Young U.S. LLP, New York, NY. 
  
Using an understanding of the problem statement or business question in scope for the client engagement, design analytics models and review design with manager. Coordinate data needs for the analysis and develop detailed execution plan including but not limited to model build, validation and harnessing insights.  Assign tasks and provide on-the-job coaching to junior team members.  Perform first level of review of the models, results and insights.  Summarize insights and results, and present to client stakeholders after manager/senior manager’s review.  Track and report progress against plan, identify issues and risks, and mitigate them with or escalate them to project leadership. Provide technical guidance and share knowledge with team members with diverse skills and backgrounds. Consistently deliver quality client services focusing on more complex, judgmental and/or specialized issues. Demonstrate technical capabilities and professional knowledge. Learn about EY and its service lines and actively assess and present ways to apply knowledge and services. 

 

Full time employment, Monday – Friday, 40 hours per week, 8:30 am – 5:30 pm. 

 

MINIMUM REQUIREMENTS:

 

Must have a Bachelor's degree in Mathematics, Information Systems, Statistics, Operations Research, Data Science, Analytics, Computer Science, Engineering, Machine Learning, or a related field and 2 years of related work experience. Alternatively, must have a Master's degree in Mathematics, Information Systems, Statistics, Operations Research, Data Science, Analytics, Computer Science, Engineering, Machine Learning, or a related field and 1 year of related work experience. 

 

Must have 1 year of experience in any combination of external advisory professional services, external consulting, or customer success. 

 

Must have 1 year hands-on working experience with artificial intelligence, machine learning, data science, or data engineering. 

 

Must have 1 year of experience working with Python. 

 

Must have 1 year of combined experience using any combination of at least 2 of the following Generative AI models and frameworks: 
o OpenAI family 
o Open source LLMs, Dall-e 
o LlamaIndex 
o Langchain 
o Retrieval Augmented Generation (RAG) 
o Other frontier model families (e.g. Anthropic) 

 

Must have 1 year of combined experience using DevOps tools GIT and Azure DevOps as well as Agile tools to develop and deploy analytical solutions with multiple features, pipelines, and releases. 

 

Must have 1 year of experience designing, building, and maintaining ML models, frameworks, and pipelines as well as designing and deploying end to end ML workflows on at least one major cloud computing platform. 

 

Must have 1 year of experience with data manipulation tools and libraries SQL, Pandas, or Spark. 

Must have 1 year of experience with containerization and scaling models as well as integrating models and feedback from downstream consumption systems. 

 

Requires travel up to 80%, of which 10% may be international, to serve client needs.

 

Employer will accept any suitable combination of education, training or experience.

 

Please apply on-line at ey.com/en_us/careers and click on "Careers - Job Search”, “See All", then “Experienced Professionals” (Job Number - 1717770).

 

What we offer

We offer a comprehensive compensation and benefits package where you’ll be rewarded based on your performance and recognized for the value you bring to the business. The base salary for this job is $139,506.00 per year. In addition, our Total Rewards package includes medical and dental coverage, pension and 401(k) plans, and a wide range of paid time off options. Join us in our team-led and leader-enabled hybrid model. Our expectation is for most people in external, client serving roles to work together in person 40-60% of the time over the course of an engagement, p